Savant 0.6.0 is Out: the first release to support Blackwell GPUs

As Blackwell GPUs become increasingly used in computer vision and video analytics, demand for their support in Savant has grown significantly. To maintain support for the widely used line of NVIDIA edge (Jetson Orin) and datacenter devices, we decided to switch Savant from using DeepStream 7.0 to a custom-built DeepStream 7.1 with TensorRT 10.9, enabling support for Blackwell GPUs.

The new Savant release received version 0.6.0. The 0.6.x release line is compatible with the previous long-term support 0.5.x line, so users should be able to migrate to newer Blackwell GPUs without code changes. However, particular models may require tweaking and modifications to work with TensorRT 10.9. Another important update in the 0.6.x line is Python 3.12 (in 0.5.x Savant used Python 3.10). This Python version is known to run faster than Python 3.10, which should improve the performance of CPU-bound workloads.

In 0.6.x, we plan to develop Savant in the same evolutionary manner as in 0.5.x: all new features go to 0.6.x, and 0.5 is frozen for new features.

The next significant Savant upgrade will transition from DeepStream 7.1 to DeepStream 8. The timeline is not defined yet, but mostly depends on the NVIDIA roadmap for supporting the entire Jetson line (Orin, Thor), DGX Spark, and top Blackwell GPUs (B300).

To use Savant 0.6.0 on discrete GPUs, you need drivers 570.133.20 or newer; on Jetson, you need JetPack 6.2.

Release notes and Docker images are available on our GitHub at the link. The documentation is updated to address new system requirements.

Do not forget to join our Discord server, where you can ask questions, promote features, and get quick help.

Choosing the technology for a computer vision product in 2025 (Part 1)

I started to apply computer vision tech in 2004 and have watched this field evolve for 20 years. As of 2025, we have built dozens of hands-on computer vision applications. Over time, they grew into the SAVANT framework, now open source.

In this article, I will cover the current and legacy tech stacks for computer vision applications. I hope this helps beginner developers make their first steps and choose their tech wisely, so they can reach their goals and stay scalable, well-performing, and up to date for at least a few years.

My name is Ivan Kudriavtsev, and I am the founder of the Savant Framework, the tech behind dozens of computer vision applications built on NVIDIA hardware. Now let’s dive into the topic!

Continue reading Choosing the technology for a computer vision product in 2025 (Part 1)

New Release Announcement: Retina RTSP Service Now Available!

We’re excited to announce the official release of Retina RTSP Service, a new addition to the Savant platform!

Retina RTSP Service enables seamless integration of real-time video streaming into your Savant-powered AI video pipelines. With Retina RTSP, you can easily ingest RTSP streams, connect them to your Savant services, and build complex computer vision solutions with minimal effort — all while maintaining low latency and high performance.

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Savant 0.5.1: DeepStream 7.0 and new features

After eight months of development, we proudly present you with Savant 0.5.1. The new Savant is based on DeepStream 7.0 (Savant 0.4 is based on DeepStream 6.4) and includes new samples (34 ready-to-use real-world samples), enhancements, and bug fixes.

We recommend using Savant 0.5.x for the production environment and new projects. Version 0.4.x becomes legacy and will not get updates except for critical bug fixes.

Continue reading Savant 0.5.1: DeepStream 7.0 and new features

Choosing A Camera For Computer Vision Wise: Resolution, Image Quality, Lens and Software

Cameras play the most important role in computer vision projects. Often, the quality of the picture captured by a camera influences way more than the sophistication of the computer vision models used in the solution. The truth is that without a proper camera, implementing a state-of-the-art solution matching business needs is often impossible. For example, facial and optical character recognition applications require high-quality, expensive cameras to deliver a pixel-perfect image to the system. Often, computer vision engineers and product sponsors/owners do not understand the characteristics and meet the situation when the solution is not even possible in the wild.

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Savant 0.4.8 is Out: A Bugfix Release

We released a minor update to Savant 0.4.x, including a bug fix found by a user. The bug concerns JSON/image/video sink adapters. The partial fix was implemented in 0.4.7.

The new release is available by the link.

Full Changelogv0.4.7…v0.4.8

Platform: DeepStream 6.4
JetPack (Jetson): 6.0

Docs: https://docs.savant-ai.io/v0.4.8/

dGPU Images:

docker pull ghcr.io/insight-platform/savant-deepstream:0.4.8-6.4
docker pull ghcr.io/insight-platform/savant-adapters-deepstream:0.4.8-6.4
docker pull ghcr.io/insight-platform/savant-adapters-gstreamer:0.4.8
docker pull ghcr.io/insight-platform/savant-adapters-py:0.4.8
docker pull ghcr.io/insight-platform/savant-deepstream-extra:0.4.8-6.4

Jetson Images:

docker pull ghcr.io/insight-platform/savant-deepstream-l4t:0.4.8-6.4
docker pull ghcr.io/insight-platform/savant-adapters-deepstream-l4t:0.4.8-6.4
docker pull ghcr.io/insight-platform/savant-adapters-gstreamer-l4t:0.4.8
docker pull ghcr.io/insight-platform/savant-adapters-py-l4t:0.4.8
docker pull ghcr.io/insight-platform/savant-deepstream-l4t-extra:0.4.8-6.4

Savant 0.4.1 is Out. Spotlight: Advanced Video Processing Features

Savant 0.4.1 continues 0.4.x release cycle, introducing several new features, multiple bug fixes, and sample updates. It is built on DeepStream 6.4 / JetPack 6.0 and widely tested on Jetson Orin Nano, Orin NX, Turing, Ampere, and Ada Lovelace discrete GPUs. In this release, we focused on testing problems that our customers and community users discovered in 0.4.0. Also, we developed an auxiliary watchdog service for pipeline health monitoring.

Continue reading Savant 0.4.1 is Out. Spotlight: Advanced Video Processing Features